• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 29 Issue 5
Oct.  2016
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Article Contents
WANG Hui, WU Mingli, LI Wenfeng, WANG Guanhong, LI Ying, TAO Xiangyu. Detection Method of Low-Frequency Oscillation in Traction Power Supply System Based on Single-Phase dq Transformation and Improved PRONY Algorithm[J]. Journal of Southwest Jiaotong University, 2016, 29(5): 878-885. doi: 10.3969/j.issn.0258-2724.2016.05.009
Citation: WANG Hui, WU Mingli, LI Wenfeng, WANG Guanhong, LI Ying, TAO Xiangyu. Detection Method of Low-Frequency Oscillation in Traction Power Supply System Based on Single-Phase dq Transformation and Improved PRONY Algorithm[J]. Journal of Southwest Jiaotong University, 2016, 29(5): 878-885. doi: 10.3969/j.issn.0258-2724.2016.05.009

Detection Method of Low-Frequency Oscillation in Traction Power Supply System Based on Single-Phase dq Transformation and Improved PRONY Algorithm

doi: 10.3969/j.issn.0258-2724.2016.05.009
  • Received Date: 04 Nov 2014
  • Publish Date: 25 Oct 2016
  • Electrical low-frequency oscillation in traction power supply systems causes vehicle traction system shutdown, which results in severe service delay. The mathematical descriptions of the oscillated voltage and current were presented based on the analysis of a large amount of measured data. The line voltage oscillation mechanism was also explained in a brief way through a simple electrical model representing the traction power supply system and locomotives. Considering the features of the single-phase power supply, the d-axis component of the line voltage was obtained by a single-phase dq transformation, and chosen as the characteristic signal and the detection object. Then, a detection method was designed based on the improved PRONY algorithm to identify the dominant pattern of low-frequency oscillation. The detection method was verified by the measured data from actual low-frequency oscillation cases. The results show that the designed detection method can identify the low-frequency oscillation with the frequency lower than 30Hz, magnitude over 0.01(p.u.), and calculate the dominant oscillation pattern and send out an alarm signal.

     

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